Measuring distance to the SDG targets – Latvia
Latvia has already achieved 22 of the 123 SDG targets for which comparable data are available and, based on most recent trends, is expected to meet 8 additional targets by 2030 (Figure 1). As virtually all OECD countries, Latvia has already met (or is close to meeting) most targets related to securing basic needs and implementing the policy tools and frameworks mentioned in the 2030 Agenda (see details in Table 1). In addition, Latvia shows a strong economic performance and it is making headway in green growth. Still, challenges remain, in particular due to its high levels of inequalities.
This country profile provides a high-level overview of some of Latvia’s strengths and challenges in performance across the SDG targets. As such, it differs in nature from Voluntary National Reviews (VNRs) or other reporting processes. To ensure international comparability, this assessment draws on the global indicator framework and relies on data sourced from the SDG Global Database and OECD databases. VNRs typically use national indicators that reflect national circumstances and are more up-to-date (See section How to read this country profile that provides some methodological details on country profiles).
Source: All data is taken and adapted from (UNDESA, 2021[1]), SDG Global Database, https://unstats.un.org/sdgs/unsdg and (OECD, 2021[2]), OECD.Stat, https://stats.oecd.org/ (accessed on 29 October 2021).
Latvia is a fast growing economy. On average, over the past 15 years, both GDP per capita and labour productivity increased by around 2.6% a year (Target 8.1). As other small OECD economies, foreign trade and foreign direct investment are an integral part of its growth model. Latvia also shows strong achievements in foreign trade with developing countries and market openness (Targets 10.a and 17.12).
Latvia has come a long way in improving its environmental performance. Implementation of the EU environmental directives and major investment have been key drivers of progress. Almost half of the country's electricity generation and of its total final energy consumption comes from renewable sources (Target 7.2). In addition, energy intensity has declined significantly over the past decade (Target 7.3), and is now around the OECD average. Changes in the energy mix and improved energy efficiency (but also to its small industrial base and relatively low incomes), GHG emissions declined in the early 2010s and have stabilised since then despite sustained economic growth (Target 13.2). When it comes to biodiversity, protected areas cover 18% of the terrestrial area and 16% of the territorial sea, above the 2020 Aichi Biodiversity Targets. In addition, virtually all the freshwater, terrestrial and marine areas that are considered as key for biodiversity are protected (Targets 14.5 and 15.1). Latvia has also implemented some of the policy instruments listed under the Planet category, including on harmful subsidies to fisheries (Target 14.6) and it already implemented legislation and regulation on listed under the Aichi Biodiversity Targets (Targets 15.8 and 15.9). While the loss of biodiversity is a global concern, the conservation status of major species in Latvia is better than in most OECD countries (Target 15.5).
Latvia reports comparatively high poverty and more could be done to foster inclusion. Latvia has one of the highest poverty rates in the OECD and this rate that has been increasing over the past decade. Relative income poverty rate was 16% in 2019, while multidimensional poverty rate was 21% (Targets 1.2 and 10.2). High levels of poverty are partly explained by the low level of redistribution (Target 10.4), with taxes and transfers reducing market income inequality by 18% while the OECD average is at 24%. They also relate to some of the shortcomings of the labour market. Average hourly earnings are only 60% of the OECD average (USD PPP 10 per hour in 2018) and the unemployment rate (8% in 2020) is above the OECD average (Target 8.5). Slightly more than 60% of the population believes that Latvia is a good place to live for ethnic and racial minorities (Target 10.3). In addition, Latvia only partially meets the criteria for migration policies to facilitate orderly, safe, regular and responsible migration and mobility of people (Target 10.7). Tackling gender equality will also require further efforts. The gender gap in unpaid work (120 minutes per day) remains high (Target 5.4) but it is in line with the OECD average. Women are underrepresented in the national and local parliaments (Targets 5.5 and 16.7), but are close to parity in the economic spheres – 44% of senior and middle management positions are held by women.
Health outcomes are poor, while out-of-pocket payments are high (Target 3.8). The distance from target on premature mortality is large (Target 3.4). The mortality rate due to suicide is well above the OECD average, and the risk of dying from non-communicable diseases (cardiovascular disease, cancer, diabetes or chronic respiratory disease) is almost twice the OECD average. Overweight and obesity are a growing concern. Around one in four adult is obese (Target 2.2). While smoking rates have been decreasing, more than 20 % of adults smoke daily (Target 3.a). Alcohol consumption remains a major public health issue, even though it fell by one quarter between 2012 and 2019 due to stricter alcohol control measures targeting younger people (Target 3.5). In addition, road traffic accidents (Target 3.6) and air pollution (Target 3.9) weigh heavily on health outcomes.
Latvia also has some distance to travel to meet some targets relating to cities (Goal 11). The overcrowding rate (at 33% in 2019) was three times the OECD average (Target 11.1). In addition, while built-up area per capita remains well below the OECD average, it increased over the past decades at the highest rate in the OECD area (Target 11.3).
Like in many other OECD countries, data availability remains a challenge when measuring distances to targets (see the Overview chapter for details). Available data on the level of the different indicators for Latvia allow covering 123 of the 169 targets. As shown in Figure 2 below, indicator coverage is uneven across the 17 goals. While six goals (within the People, Planet and Prosperity categories) have most of their targets covered (the indicator coverage exceeds 80%), coverage is much lower for Goal 13 on climate action and Goal 11 on cities, with only 40% of targets covered. Data gaps become starker when focusing on performance indicators, excluding those providing contextual information. In this case, coverage exceeds 80% for only two goals, i.e. Goal 3 on health and Goal 4 on education. For seven goals, mostly related to the Planet category (Goals 13, 14 and 15) but also to gender inequality, cities, and partnerships (Goals 5, 11 and 17), data are lacking to monitor progress over time for more than two in three targets.
Note: The figure represents Latvia's share of targets covered by at least one indicator for each SDG. Numbers from 1 to 17 stand for the goals: 1 No poverty, 2 Zero hunger, 3 Good health and well-being, 4 Quality education, 5 Gender equality, 6 Clean water and sanitation, 7 Affordable and clean energy, 8 Decent work and economic growth, 9 Industry, innovation and infrastructure, 10 Reduced inequalities, 11 Sustainable cities and communities, 12 Responsible consumption and production, 13 Climate action, 14 Life below water, 15 Life on land, 16 Peace, justice and strong institutions and 17 Partnerships for the goals. These goals are grouped under five broad themes (the “5Ps”): People, Planet, Prosperity, Peace and Partnership. Beyond data availability, other statistical gaps such as timeliness or granularity also need to be considered. For instance, given the lag in available data, the effects of the pandemic on current distance and trajectories may not be reflected in the estimates.
Source: All data is taken and adapted from (UNDESA, 2021[1]), SDG Global Database, https://unstats.un.org/sdgs/unsdg and (OECD, 2021[2]), OECD.Stat, https://stats.oecd.org/ (accessed on 29 October 2021).
While some SDG Targets are, on average, close to being met, performance is very uneven across the 17 Goals of the 2030 Agenda for Sustainable Development. Table 1 presents an overview of Latvia’s progress towards targets based on available data for each of the 17 Goals. It shows that distances to Targets and trends over time differ significantly even when considering a specific goal.
The OECD report The Short and Winding Road to 2030: Measuring Distance to the SDG Targets evaluates the distance that OECD countries need to travel to meet SDG targets for which data are currently available. It also looks at whether countries have been moving towards or away from these targets, and how likely they are to meet their commitments by 2030, based on an analysis of recent trends and the observed volatility in the different indicators.
As most authors and international organisations, this report adopts a rather simple geometric growth model for assessing the direction and pace of recent changes in the context of the SDGs. Yet, instead of making direct estimates of the value of the indicator by 2030, it models the likelihood of achieving a specific level using Monte Carlo simulations.
While the report provides an overview of where OECD countries, taken as a whole, currently stand, country profiles provide details of the performance and data availability of individual OECD countries.
How to read the OECD SDG Wheel?
Progress on SDGs requires a granular understanding of countries’ strengths and weaknesses based on the consideration of the 169 targets of the 2030 Agenda. Figure 1 shows both current achievements (in the inner circle; the longer the bar, the smaller the distance remaining to be travelled) as well as whether OECD countries are on track (or are at least making progress) to meet their commitments by 2030 (in the outer circle).
The length of each bar shows current level of achievement on each target. As detailed in the Methodological Annex, countries’ distance to target is measured as the “standardised difference” between a country’s current position and the target end-value. For each indicator, the standardised measurement unit (s.u.) is the standard deviation observed among OECD countries in the reference year (i.e. the year closest to 2015). Therefore, the longer the bar, the shorter the distance still to be travelled to reach the target by 2030. The colours of the bars applied to the various targets refer to the goals they pertain to.
The outer ring shows how OECD countries are performing over time and how likely they are to meet the different targets by 2030 based on the observed trends of the various indicators. It uses stoplight colours to classify the progress towards the target:
green is used to indicate those countries that (based on the change in the different indicators over a recent period) should meet the target in 2030 just by maintaining their current pace of progress (i.e. more than 75% of (randomised) projections meet the target);
yellow for those countries whose current pace of progress is insufficient to meet the target by 2030 (i.e. less than 75% of randomised projections meet the target, while the correlation coefficient between the indicator and the year is high and statistically significant, implying that a significant trend could be detected); and
red for those countries whose recent changes have been stagnating or moving them further away from the target (i.e. less than 75% of randomised projections meet the target and the correlation coefficient between the indicator and the year is low or statistically insignificant, implying that no statistical trend could be identified).
How to read the Strength and Challenges sections?
With the aim of helping its member countries in navigating the 2030 Agenda and in setting their own priorities for action, this report relies on a unique methodology for measuring the distance that OECD countries have to travel to achieve SDG targets. The identification of the main strengths and challenges proposed in this report relies on current performances only:
A target is considered to be a strength when the distance to the target end-value is lower than 0.5 s.u. (i.e. the distance is deemed to be small) or when the country is closer to the target than the OECD average. For instance, while Korea's distance to Target 2.2 on malnutrition is 1.4 s.u. (i.e. classified as medium distance), the average OECD distance is 2.5 s.u. Therefore, Target 2.2 is categorised as being a strength for Korea.
A target is considered to be a challenge when the distance to target is greater than 1.5 s.u. (i.e. distance is deemed to be long) or when the country is further away from the target than the OECD average. For instance, Estonia's distance to Target 4.2 on pre-primary education is 1.1 s.u. (i.e. medium distance), which is higher than the 0.24 s.u. distance for the OECD average. Target 4.2 is therefore classified as a weakness for Estonia.
While the lack of consistent time series often prevents an exhaustive assessment of trends, they are discussed when available and relevant in nuancing the assessment of current performance.
How to read the Statistical Gaps section?
In total, this report relies on 537 data series supporting 183 of the 247 indicators listed in the global indicator framework (or for close proxies of these indicators). These indicators cover 134 of the 169 SDG targets. Yet, target coverage is uneven across the 17 goals and among OECD member countries.
Figure 2 summarises data availability:
darker blue bars indicate the share of targets for which at least one indicator (including indicators providing context information) is available
lighter blue bars indicate the share of targets for which the available indicator(s) include those having a clear normative direction (i.e. allowing to distinguish between good and bad performance), which are the only ones used to measure distances to target levels.
medium blue bars indicate the share of targets for which progress over time can be gauged (i.e. at least three observations are available over a five-year period).
All methods and concepts are further detailed in the Methodological Annex.